A New Class of Policies in Vector-Valued Markov Decision Processes

For a vector-valued Markov decision process with discounted reward criterion, we introduce a new class of policies called the semi-stationary policies and show that an optimal semi-stationary policy that attains the extreme points of the set of rewards induced by all policies can be described as a combination of optimal stationary policies.